Activity Recognition

Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.

Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 721–730 of 1322 papers

Title	Date	Tasks	Status	Hype
Neural Style Transfer Enhanced Training Support For Human Activity Recognition	Jul 27, 2021	Activity RecognitionData Augmentation	—Unverified	0
A Neurorobotics Approach to Behaviour Selection based on Human Activity Recognition	Jul 27, 2021	Activity RecognitionDecision Making	—Unverified	0
Inference for Change Points in High Dimensional Mean Shift Models	Jul 19, 2021	Activity Recognitionvalid	—Unverified	0
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People Grouping	Jul 17, 2021	Action RecognitionActivity Recognition	CodeCode Available	0
Let's Play for Action: Recognizing Activities of Daily Living by Learning from Life Simulation Video Games	Jul 12, 2021	Action ClassificationActivity Recognition	CodeCode Available	1
Human-like Relational Models for Activity Recognition in Video	Jul 12, 2021	Activity Recognition	—Unverified	0
A Light-weight Deep Human Activity Recognition Algorithm Using Multi-knowledge Distillation	Jul 6, 2021	Activity RecognitionClassification	—Unverified	0
Early Mobility Recognition for Intensive Care Unit Patients Using Accelerometers	Jun 28, 2021	Activity RecognitionFeature Engineering	—Unverified	0
Reducing numerical precision preserves classification accuracy in Mondrian Forests	Jun 28, 2021	Activity RecognitionClassification	CodeCode Available	0
Human Activity Recognition using Continuous Wavelet Transform and Convolutional Neural Networks	Jun 23, 2021	Activity RecognitionHuman Activity Recognition	CodeCode Available	0

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All datasets RWF-2000 Stanford40 First-Person Hand Action Benchmark Self-stimulatory Behavior Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Structured Keypoint Pooling	Accuracy	93.4	—	Unverified
2	Semi-Supervised Hard Attention (SSHA); pretrained on Deepmind Kinetics dataset	Accuracy	90.4	—	Unverified
3	Human Skeletons + Change Detection	Accuracy	90.25	—	Unverified
4	Separable Convolutional LSTM	Accuracy	89.75	—	Unverified
5	SPIL Convolution	Accuracy	89.3	—	Unverified
6	Flow Gated Network	Accuracy	87.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FocusCLIP	Top-3 Accuracy (%)	10.47	—	Unverified
2	CLIP	Top-3 Accuracy (%)	6.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Boutaleb et al.	1:1 Accuracy	97.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	all-landmark-model	Activity Recognition	0.76	—	Unverified